Privatdoz. DI Dr.
CMS Physics Analysis
Telephone: +43 (1) 51581 - 2813
At HEPHY in Vienna I have started an analysis group that searches for signs of supersymmetry at CMS. In the last few years, though, I have focussed on the interpretation of the search results: given a positive or a null result, what are its implications? What do the data really tell us about supersymmetry, or other theories, and the question of naturalness?
To this end I founded a small collaboration, and together we developed "SModelS", a software framework that allows us to confront an arbitrary theoretical model with LHC results.
It is my ultimate vision that we can learn the fundamental physical laws beyond the Standard Model in an unsupervised fashion, employing modern machine learning techniques.
Also in data analysis I work at advancing novel machine learning techniques such as multi-level optimization, deep neural networks, and information geometry.
At times, my physics colleagues and I even manage to contribute back to the statistics and machine learning communites.
An older research interest of mine is the reconstruction of interaction vertices. This effort has resulted in the creation of a reconstruction toolkit "RAVE", that is currently in use in the Belle2 experiment.
- 2001 Diploma Thesis, "Towards 2D Quantum Gravity With Fermions", TU Wien
- 2001 Data scientist at HEPHY
- 2001 Joined CMS Collaboration, CERN
- 2004 PhD Thesis, "Development of Vertex Finding and Fitting Algorithms for CMS", TU Wien
- 2004 - 2008 PostDoc Position at HEPHY, working on b-tagging and vertexing for CMS, ILC
- 2008 Faculty position at HEPHY
- 2009 - 2012 Lead Vienna HEPHY Search Group for SUSY
- 2012 Founded SModelS collaboration
- 2014 Project Leader, "Interpretation of LHC Data with Simplified Models"
- 2015 Guest professor at Universidade de São Paolo
- 2018 "Venia docendi" at University of Vienna
2014-2017: Austrian Science Fund Project P26896-N27, "Interpretation of LHC Data with Simplified Models"
- Federico Ambrogi, 2014 -- 2018
- Matthias Wolf, February 2018 -- ongoing
- Felix Wagner, July 2020 -- ongoing
Master and Diploma Theses (most recent):
- Michael Traub, New Data Standard for the SModelS Database Containing LHC Results for Supersymmetry Searches, TU Wien, Oct. 2015
- Veronika Magerl, Constraining Low Fine Tuned Supersymmetric Models with Simplified Models Spectra Results Based on CMS and ATLAS Searches, TU Wien, July 2015
- Ursula Laa, Interpretation of the CMS and ATLAS Simplified Models Results, Uni Wien, 2014
- Doris Proschofsky-Spindler, Development of a Framework for Interpretation of LHC Data Based on Simplified Models, TU Wien, January 2014
Suchita Kulkarni, 2014 -- 2017
Lectures at TU Wien / Universität Wien:
- WS 2015/2016
- 142.094, 260129, Lecture "Astro-particle physics", with Claudia Wulz
- WS 2016/2017
- 142.094, 260129, Lecture "Astro-particle physics", with Manfred Jeitler
- WS 2017/2018
- Summer 2018
- Lecture series, "Machine learning in particle physics", DKPI summer school
- WS 2018/2019
- WS 2019/2020
- 260032,142.340,142.351, Vorlesung und Übungen, "Statistische Methoden der Datenanalyse"
"Über den Anfang des Universums. Einige gelöste Rätsel und offene Fragen". Katholisches Bildungswerk Ebensee, OÖ, November 2014.
- A complete list of my publications (>800, as of april 2018) is here.
- h-Index: 70 (web of science, april 2018).
Ambrogi, Federico; Kraml, Sabine; Kulkarni, Suchita; Laa, Ursula; Lessa, Andre et al. [..] (2018) SModelS v1.1 user manual: Improving simplified model constraints with efficiency maps. Comput. Phys. Commun., Bd. 227, S. 72-98.
Kraml, S.; Kulkarni, S.; Laa, U.; Lessa, A.; Magerl, V. et al. [..] (2014) SModelS v1.0: a short user guide. Bericht-Nr. HEPHY-PUB-945-14, LPSC13295, arXiv:1412.1745;.
Kraml, S.; Kulkarni, S.; Laa, U.; Lessa, A.; Magerl, W. et al. [..] (2014, online: 2014) SModelS: a tool for interpreting simplified-model results from the LHC and its application to supersymmetry. The European Physical Journal C, Bd. 74 (2014), S. 2868.
Collaboration, CMS; Chatrchyan, S.; ..; Adam, W.; Aguilo, E. et al. [..] (2013) Interpretation of searches for supersymmetry with simplified models. Physical Review D, Bd. 88 (2013), S. 052017.
Alves, D.; Arkani-Hamed, N.; Sanjay, A.; ..; Waltenberger, W. et al. [..] (2012) Simplified models for LHC new physics searches. Journal of Physics G, Bd. 39, S. 105005.
Waltenberger, W. (2011) RAVE - a detector-independent toolkit toreconstruct vertices. IEEE Transactions on Nuclear Science (58 (2011)), S. 434-444.
Waltenberger, W. (2008) Adaptive Vertex Reconstruction. Bericht-Nr. CMS Note 2008/033; CERN:.
Waltenberger, W.; Frühwirth, R.; Vanlaer, P. (2007) Adaptive vertex fitting. Journal of Physics G, Bd. N343-N356 (Nucl. Part. Phys. 34), S. 18.
Speer, T.; Frühwirth, R.; Vanlaer, P.; Waltenberger, W. (2006) Robust vertex fitters. Nuclear Instruments and Methods in Physics Research A, Bd. 566, S. 149 - 152.